def main():
distance_list = []
expected_of_R_2_sum_list = []
expected_of_R_4_sum_list = []
steps_list = []
M = 350000
for steps in range(10, 35, 5):
distance_list = []
for walker_number in range(0, M):
a = RandomChain(0, 0, 0)
x, y, z = a.add_X_spheres(steps)
distance_squared = math.sqrt(x ** 2 + y ** 2 + z ** 2)
distance_list.append(distance_squared)
expected_of_R_2_sum = 0
expected_of_R_4_sum = 0
for distance_square in distance_list:
expected_of_R_2_sum = expected_of_R_2_sum + distance_square
expected_of_R_4_sum = expected_of_R_4_sum + distance_square ** 2
expected_of_R_2_sum = expected_of_R_2_sum / M
expected_of_R_4_sum = expected_of_R_4_sum / M
expected_of_R_2_sum_list.append(expected_of_R_2_sum)
expected_of_R_4_sum_list.append(expected_of_R_4_sum)
steps_list.append(steps)
delta = math.sqrt((expected_of_R_4_sum - expected_of_R_2_sum) / M)
print "expected_of_R_2_sum: " + str(expected_of_R_2_sum)
print "expected_of_R_4_sum: " + str(expected_of_R_4_sum)
print "delta: " + str(delta)
best_line(np.log(steps_list), np.log(expected_of_R_2_sum_list))
def main():
distance_list = []
expected_of_R_2_sum_list = []
expected_of_R_4_sum_list = []
steps_list = []
M = 350000
for steps in range(10, 40, 5):
distance_list = []
for walker_number in range(0, M):
walker = Randomwalker(0, 0)
x, y = walker.walk_X_steps(steps)
distance_squared = math.sqrt(x ** 2 + y ** 2)
distance_list.append(distance_squared)
expected_of_R_2_sum = 0
expected_of_R_4_sum = 0
for distance_square in distance_list:
expected_of_R_2_sum = expected_of_R_2_sum + distance_square
expected_of_R_4_sum = expected_of_R_4_sum + distance_square ** 2
expected_of_R_2_sum = expected_of_R_2_sum / M
expected_of_R_4_sum = expected_of_R_4_sum / M
expected_of_R_2_sum_list.append(expected_of_R_2_sum)
expected_of_R_4_sum_list.append(expected_of_R_4_sum)
steps_list.append(steps)
delta = math.sqrt((expected_of_R_4_sum - expected_of_R_2_sum) / M)
print "expected_of_R_2_sum: " + str(expected_of_R_2_sum)
print "expected_of_R_4_sum: " + str(expected_of_R_4_sum)
print "delta: " + str(delta)
best_line(steps_list, expected_of_R_2_sum_list)
